$L_{1}$ Adaptive Control of a Dual-Rotor Tail-Sitter Unmanned Aerial Vehicle With Input Constraints During Hover Flight

Abstract

The input constraints of control surfaces may lead to saturations, which could limit the achievable performance or even cause instability of vertical take-off and landing (VTOL) tail-sitter unmanned aerial vehicle (UAV). To improve flight safety and attitude tracking performance, a novel L 1 adaptive control architecture for attitude tracking of a tail sitter subjected to input constraints is proposed in this study. The imprecise mathematical model, low weight, and small size all present different challenges when designing a control system. In this work, a feedforward compensator is first used to narrow down the uncertain bounds with the consideration of finite accuracy from prior knowledge. Second, according to the linearized model, a baseline controller is designed to offer basic performance for a nominal system without uncertainty. Finally, the L 1 adaptive controller is developed to compensate for unmatched uncertainties based on the control system developed before. The stability and performance bounds of the closed-loop system are analyzed to illustrate the impact of input constraints. The numerical simulations and flight tests are carried out to verify the improved attitude tracking performance when input saturation exists.

Double Hybrid Tailsitter Unmanned Aerial Vehicle With Vertical Takeoff and Landing

“…Some of them use a simple configuration, easier to manufacture with a rectangular wing [39], [44], and oth- ers use positive curling on the leading edge, in order to improve aerodynamics [6], [31], [36], [46]. We also found tailsitters with positive full-wing bending, which seek the best performance in horizontal flight aerodynamics [48].…”

System Identification and Control for a Tail-Sitter Unmanned Aerial Vehicle in the Cruise Flight

“…Measurements can be taken to predict and reduce any unwanted wind disturbance [23]. Special treatment on the controller can be designed to improve the robustness and stability under a windy condition [24,25]. In the transition period, the optimization method has been applied to the altitude variation and energy consumption in [26,27].…”